What are the different techniques of data mining and explain the ETL process?
Object-Oriented Programming (OOP) views software as a collection of interacting objects, each with its own data and behavior. It's well-suited for modeling real-world entities and complex systems. For example, a car is an object with properties like color and speed, and it can do things like start aRead more
Object-Oriented Programming (OOP) views software as a collection of interacting objects, each with its own data and behavior. It’s well-suited for modeling real-world entities and complex systems. For example, a car is an object with properties like color and speed, and it can do things like start and stop. This approach is particularly effective in scenarios demanding complex systems with interrelated components. For example, graphical user interfaces and large scale enterprise applications.
Functional Programming (FP) treats computation as the evaluation of mathematical functions. It uses functions that take inputs and produce outputs. Think of a calculator: you input numbers, and it outputs the result. It is used in applications requiring high levels of testability and efficiency. E.g., financial systems, data analysis, parallel computing, etc.
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Data Mining Techniques Classification: Assigns items to predefined categories or classes. Common algorithms include decision trees, support vector machines, and neural networks. Clustering: Groups similar items together based on their features. K-means and hierarchical clustering are popular methodsRead more
Data Mining Techniques
ETL Process
Together, these techniques and processes enable effective data analysis, helping to uncover patterns, relationships, and insights from large datasets.
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